Abstract: Within the last decade, several industrialized countries have stressed the importance of advanced manufacturing, such as 3D Printing (3DP), to their economies. The combination of rigorous material modeling theories and robotic control, coupled with dramatic increases of computational power, can potentially play a significant role in the analysis and design of many emerging, multistage, additive manufacturing systems. The goal of these systems is to build structures that are otherwise extremely difficult or impossible to construct using classical manufacturing methods. Ultimately, the objective of 3DP is to develop superior products, manufactured at lower overall operational costs. In many emerging 3DP systems, such processes involve attaching multi-material dispensers to robots, which then release functionalized, complex, multiphase, material mixtures in free-space. These approaches are becoming popular because they utilize preexisting widely-available, highly-programmable, robots, which have been developed for decades. However, often the release of a complex mixture in free-space is imprecise, thus electromagnetic field control has been proposed as one possible remedy to enhance the precision of such processes, by rapidly guiding the material to a desired target position. Thereafter, lasers are used to irradiate the deposited material to a desired state. The outline of this presentation is:
· To develop Machine Learning Algorithms to ascertain the appropriate combination of system parameters: robot kinematics, electromagnetic fields, laser-intensities, etc, needed to create desired complex structures.
· To present detailed modeling of the dynamic deposition of complex mixtures(Discrete Element Methods)
· To present detailed of modeling of laser processing of deposited mixtures (Computational Optics) and
· To present detailed modeling of continuum material behavior/performance (Digital-Image Computation).